Communication system with receivers employing generalized two-stage data estimation

ABSTRACT

A wireless transmit/receive unit (WTRU) is configure to receive and sample wireless signals in a shared spectrum where the wireless signal comprise encoded symbols. The WTRU has a channel estimation device configured to process received signal samples to produce an estimate of a channel response of the received signals corresponding to a matrix H. The channel estimation device is preferably configured to process the received signal samples to produce an estimate of noise variance of the received signals. The WTRU preferably has a two stage data estimator that includes a channel equalizer and a despreader. The channel equalizer is configured to process received signal samples using the estimated channel response matrix H and the estimate of noise variance to produce a spread signal estimate of the received signals. The despreader is configured to process the spread signal estimate of the received signals produced by said channel equalizer to recover encoded symbols of the received signals.

CROSS REFERENCE TO RELATED APPLICATION(S)

This application is a continuation of U.S. patent application Ser. No.11/455,999, filed Jun. 20, 2006, now U.S. Pat. No. 7,386,033, which is acontinuation of U.S. patent application Ser. No. 11/138,816, filed May26, 2005, now U.S. Pat. No. 7,079,570, which is a continuation of U.S.patent application Ser. No. 10/753,631, filed Jan. 8, 2004, now U.S.Pat. No. 6,937,644, which claims priority from U.S. ProvisionalApplication No. 60/439,284, filed Jan. 10, 2003, which are incorporatedby reference herein.

FIELD OF INVENTION

The present invention relates to wireless communication systems. Moreparticularly, the present invention is directed to data estimation insuch systems.

BACKGROUND

In wireless systems, joint detection (JD) is used to mitigateinter-symbol interference (ISI) and multiple-access interference (MAI).JD is characterized by good performance but high complexity. Even usingapproximate Cholesky or block Fourier transforms with Choleskydecomposition algorithms, the complexity of JD is still very high. WhenJD is adopted in a wireless receiver, its complexity prevents thereceiver from being implemented efficiently. This evidences the need foralternative algorithms that are not only simple in implementation butalso good in performance.

To overcome this problem, prior art receivers based on a channelequalizer followed by a code despreader have been developed. These typesof receivers are called single user detection (SUD) receivers because,contrary to JD receivers, the detection process does not require theknowledge of channelization codes of other users. SUD tends to notexhibit the same performance as JD for most data rates of interest, eventhough its complexity is very low. Accordingly, there exists a need forlow complexity high performance data detectors.

SUMMARY

A wireless transmit/receive unit (WTRU) is configured to receive andsample wireless signals in a shared spectrum where the wireless signalscomprise encoded symbols. The WTRU has a channel estimation deviceconfigured to process received signal samples to produce an estimate ofa channel response of the received signals corresponding to a matrix H.The channel estimation device is further configured to process thereceived signal samples to produce an estimate of noise variance of thereceived signals. The WTRU has a two stage data estimator that includesa channel equalizer and a despreader. The channel equalizer isconfigured to process received signal samples using the estimatedchannel response matrix H and the estimate of noise variance to producea spread signal estimate of the received signals. The despreader isconfigured to process the spread signal estimate of the received signalsproduced by said channel equalizer to recover encoded symbols of thereceived signals.

Preferably, codes of the signals are processed using a block Fouriertransform (FT), producing a code block diagonal matrix. A channelresponse matrix is estimated. The channel response matrix is extendedand modified to produce a block circulant matrix, and a block FT istaken producing a channel response block diagonal matrix. The code blockdiagonal matrix is combined with the channel response block diagonalmatrix. The received signals are sampled and processed using thecombined code block diagonal matrix and channel response block diagonalmatrix with a Cholesky algorithm. A block inverse FT is performed on aresult of the Cholesky algorithm to produce spread symbols. The spreadsymbols are despread to recover symbols of the received signals.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a two stage data detection.

FIG. 2 is a block diagram of an embodiment of two-stage data detection.

FIG. 3 is a block diagram of code assignment to reduce the complexity oftwo-stage data detection.

FIGS. 4A-4D are block diagrams of utilizing look-up tables to determineΛ_(R).

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention will be described with reference to the drawingfigures where like numerals represent like elements throughout.

A two stage data estimator can be used in a wireless transmit/receiveunit (WTRU) or base station, when all of the communications to bedetected by the estimator experience a similar channel response.Although the following is described in conjunction with the preferredproposed third generation partnership project (3GPP) wideband codedivision multiple access (W-CDMA) communication system, it is applicableto other systems.

FIG. 1 is a simplified block diagram of a receiver using a two stagedata estimator 55. An antenna 50 or antenna array receives radiofrequency signals. The signals are sampled by a sampling device 51,typically at the chip rate or at a multiple of the chip rate, producinga received vector r. A channel estimation device 53 using a referencesignal, such as a midamble sequence or pilot code, estimates the channelresponse for the received signals as a channel response matrix H. Thechannel estimation device 53 also estimates the noise variance, σ².

The channel equalizer 52 takes the received vector r and equalizes itusing the channel response matrix H and the noise variance σ², producinga spread symbol vector s. Using codes C of the received signals, adespreader 54 despreads the spread symbol vector s, producing theestimated symbols d.

With joint detection (JD), a minimum mean square error (MMSE) formulawith respect to the symbol vector d can be expressed as:{circumflex over (d)}=(A ^(H) R _(n) ⁻¹ A+R _(d) ⁻¹)⁻¹ A ^(H) R _(n) ⁻¹r,  Equation (1)or{circumflex over (d)}=R _(d) A ^(H)(AR _(d) A ^(H) +R _(n))⁻¹r,  Equation (2)where {circumflex over (d)} is the estimate of d, r is the receivedsignal vector, A is the system matrix, R_(n) is the covariance matrix ofnoise sequence, R_(d) is the covariance matrix of the symbol sequenceand the notation (.)^(H) denotes the complex conjugate transpose(Hermitian) operation. The dimensions and structures of the abovevectors and matrixes depend on specific system design. Usually,different systems have different system parameters such as framestructure, length of data field and length of delay spread.

The matrix A has different dimensions for different systems, and thedimensions of matrix A depend on the length of data field, number ofcodes, spreading factor and length of delay spread. By way of example,for the transmission of 8 codes with spreading factor of 16 each, thematrix A has dimensions of 1032 by 488 for a WCDMA TDD system if bursttype 1 is used and for a delay spread of 57 chips long, while matrix Ahas dimensions of 367 by 176 for TD-SCDMA system for a delay spread of16 chips long.

Assuming white noise and uncorrelated symbols with unity energy,R_(n)=σ²I and R_(d)=I, where I denotes the identity matrix. Substitutionof these into Equations 1 and 2 results in:{circumflex over (d)}=(A ^(H) A+σ ² I)⁻¹ A ^(H) r,  Equation (3)or{circumflex over (d)}=A ^(H)(AA ^(H)+σ² I)⁻¹ r.  Equation (4)

The received signal can be viewed as a composite signal, denoted by s,passed through a single channel. The received signal r may berepresented by r=Hs, where H is the channel response matrix and s is thecomposite spread signal. H takes the form of:

$\begin{matrix}{\underset{\_}{H} = {\begin{bmatrix}h_{0} & \; & \; & \; & \; & \; & \; & \; \\h_{1} & h_{0} & \; & \mspace{11mu} & \; & \; & \; & \; \\\vdots & h_{1} & \vdots & \; & \; & \; & \; & \; \\\vdots & \vdots & \vdots & \vdots & \; & \; & \; & \; \\h_{W - 1} & \vdots & \; & \vdots & {\vdots\;} & \; & \; & \; \\\; & h_{W - 1} & \; & \; & \vdots & \vdots & \; & \; \\\; & \; & \vdots & \; & \; & \vdots & \vdots & \; \\\; & \; & \; & \vdots & \; & \; & \vdots & h_{0} \\\; & \; & \; & \; & \vdots & \; & \; & h_{1} \\\; & \; & \; & \; & \; & \vdots & \; & \vdots \\\; & \; & \; & \; & \; & \; & \vdots & \vdots \\\; & \; & \; & \; & \; & \; & \; & h_{W - 1}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(5)}\end{matrix}$

In Equation (5), W is the length of the channel response, and istherefore equal to the length of the delay spread. Typically W=57 forW-CDMA time division duplex (TDD) burst type 1 and W=16 for timedivision synchronous CDMA (TD-SCDMA). The composite spread signal s canbe expressed as s=Cd, where the symbol vector d is:d=(d₁,d₂, . . . ,d_(KN) _(s) )^(T),  Equation (6)and the code matrix C is:C=└C⁽¹⁾,C⁽²⁾, . . . ,C^((K))┘  Equation (7)with:

$\begin{matrix}{C^{(k)} = {\begin{bmatrix}c_{1}^{(k)} & \; & \; & \; & \; & \; & \; & \; \\\vdots & \; & \; & \; & \; & \; & \; & \; \\c_{Q}^{(k)} & \; & \; & \; & \; & \; & \; & \; \\\vdots & c_{1}^{(k)} & \; & \; & \; & \; & \; & \; \\\; & \vdots & \; & \; & \; & \; & \; & \; \\\; & {\; c_{Q}^{(k)}} & \vdots & \; & \; & \; & \; & \; \\\; & \; & \; & \vdots & \; & \; & \; & \; \\\; & \; & \; & \; & \vdots & \; & \; & \; \\\; & \; & \; & \; & \; & \vdots & \; & \; \\\; & \; & \; & \; & \; & \; & \vdots & c_{1}^{(k)} \\\; & \; & \; & \; & \; & \; & \; & \vdots \\\; & \; & \; & \; & \; & \; & \; & c_{Q}^{(k)}\end{bmatrix}.}} & {{Equation}\mspace{14mu}(8)}\end{matrix}$

Q, K and N_(s) denote the spread factor (SF), the number of active codesand the number of symbols carried on each channelization code,respectively. c_(i) ^((k)) is the i^(th) element of the k^(th) code. Thematrix C is a matrix of size N_(s)·Q by N_(s)·K.

Substitution of A=HC into Equation (4) results in:{circumflex over (d)}=C ^(H) H ^(H)(HR _(c) H ^(H) +σ ² I)⁻¹ r  Equation(9)where R_(c)=CC^(H). If ŝ denotes the estimated spread signal, Equation(9) can be expressed in two stages:

Stage 1:ŝ=H ^(H)(HR _(C) H ^(H) +σ ² I)⁻¹ r  Equation (10)

Stage 2:{circumflex over (d)}=C ^(H) ŝ.  Equation (11)

The first stage is the stage of generalized channel equalization. Itestimates the spread signal s by an equalization process per Equation10. The second stage is the despreading stage. The symbol sequence d isrecovered by a despreading process per Equation 11.

The matrix R_(c) in Equation 9 is a block diagonal matrix of the form:

$\begin{matrix}{{R_{C} = \begin{bmatrix}R_{0} & \; & \; & \; \\\; & R_{0} & \; & \; \\\; & \; & ⋰ & \; \\\; & \; & \; & R_{0}\end{bmatrix}},} & {{Equation}\mspace{14mu}(12)}\end{matrix}$

The block R₀ in the diagonal is a square matrix of size Q. The matrixR_(c) is a square matrix of size N_(s)·Q.

Because the matrix R_(c) is a block circular matrix, the block FastFourier transform (FFT) can be used to realize the algorithm. With thisapproach the matrix R_(c) can be decomposed as:R _(c) =F _((Q)) ⁻¹Λ_(R) F _((Q))  Equation (13)withF _((Q)) =F _(Ns) {circle around (×)}I _(Q),  Equation (14)

where F_(Ns) is the N_(s)-point FFT matrix, I_(Q) is the identity matrixof size Q and the notation {circle around (×)} is the Kronecker product.By definition, the Kronecker product Z of matrix X and Y, (Z=X{circlearound (×)}Y) is:

$\begin{matrix}{{Z = \begin{bmatrix}{x_{11}Y} & {x_{12}Y} & \ldots & {x_{1N}Y} \\{x_{21}Y} & {x_{21}Y} & \; & {x_{2N}Y} \\\vdots & \; & ⋰ & \; \\{x_{M\; 1}Y} & {x_{M\; 1}Y} & \; & {x_{MN}Y}\end{bmatrix}},} & {{Equation}\mspace{14mu}(15)}\end{matrix}$where x_(m,n) is the (m,n)^(th) element of matrix X. For each F_((Q)), aNs-point FFT is performed Q times. Λ_(R) is a block-diagonal matrixwhose diagonal blocks are F_((Q))R_(C)(:,1:Q). That is,diag(Λ_(R))=F _((Q)) R _(C)(:,1:Q),  Equation (16)where R_(C)(:,1:Q) denotes the first Q columns of matrix R_(C).

The block circular matrix can be decomposed into simple and efficientFFT components, making a matrix inverse more efficient and less complex.Usually, the large matrix inverse is more efficient when it is performedin the frequency domain rather than in a time domain. For this reason,it is advantageous to use FFT and the use of a block circular matrixenables efficient FFT implementation. With proper partition, the matrixH can be expressed as an approximate block circular matrix of the form:

$\begin{matrix}{{H = \begin{bmatrix}H_{0} & \; & \; & \; \\H_{1} & H_{0} & \; & \; \\H_{2} & H_{1} & \; & \; \\\vdots & H_{2} & \; & \; \\H_{L - 1} & \vdots & \; & \; \\\; & H_{L - 1} & ⋰ & H_{0} \\\; & \; & \; & H_{1} \\\; & \; & \; & H_{2} \\\; & \; & \; & \vdots \\\; & \; & \; & H_{L - 1}\end{bmatrix}},} & {{Equation}\mspace{14mu}(17)}\end{matrix}$where each H_(i), i=0,1,. . . ,L−1 is a square matrix of size Q. L isthe number of data symbols affected by the delay spread of propagationchannel and is expressed as:

$L = {\lceil \frac{Q + W - 1}{Q} \rceil.}$

The block circular matrix H_(C) is obtained by expanding the columns ofmatrix H in Equation (17) by circularly down-shifting one element blocksuccessively.

The matrix H_(C) can be decomposed by block FFT as:H _(C) =F _((Q)) ⁻Λ_(H) F _((Q)),  Equation (20)where Λ_(H) is a block-diagonal matrix whose diagonal blocks areF_((Q))H_(C)(:,1:Q); anddiag(Λ_(H))=F _((Q)) H _(C)(:,1:Q),  Equation (21)where H_(C)(:,1:Q) denotes the first Q columns of matrix H_(C).

From Equation (20), H_(C) ^(H) can be defined asH _(C) ^(H) =F _((Q)) ⁻¹Λ_(H) ^(H) F _((Q)).  Equation (22)

Substituting matrix R_(c) and H_(C) into Equation 10, ŝ is obtained:ŝ=F _((Q)) ⁻¹Λ_(H) ^(H)(Λ_(H)Λ_(R)Λ_(H) ^(H)+σ² I)⁻¹ F _((Q))r.  Equation (23)

For a zero forcing (ZF) solution, equation 19 is simplified toŝ=F _((Q)) ⁻¹Λ_(R) ⁻¹Λ_(H) ⁻¹ F _((Q)) r.  Equation (24)

The matrix inverse in Equations (23) and (24) can be performed usingCholesky decomposition and forward and backward substitutions.

In a special case of K=SF (where the number of active codes equals thespreading factor), the matrix R_(C) becomes a scalar-diagonal matrixwith identical diagonal elements equal to the SF. In this case,Equations (10) and (11) reduce to:

$\begin{matrix}{{\hat{\underset{\_}{s}} = {{H^{H}( {{HH}^{H} + {\frac{\sigma^{2}}{Q}I}} )}^{- 1}\underset{\_}{r}}}{and}} & {{Equation}\mspace{14mu}(25)} \\{\hat{\underset{\_}{d}} = {\frac{1}{Q}C^{H}{\hat{\underset{\_}{s}}.}}} & {{Equation}\mspace{14mu}(26)}\end{matrix}$

Equation (25) can also be expressed in the form of:

$\begin{matrix}{\hat{\underset{\_}{s}} = {( {{H^{H}H} + {\frac{\sigma^{2}}{Q}I}} )^{- 1}H^{H}{\underset{\_}{r}.}}} & {{Equation}\mspace{14mu}(27)}\end{matrix}$

With FFT, Equations (25) and (27) can be realized by:

$\begin{matrix}{{\hat{\underset{\_}{s}} = {F^{- 1}{\Lambda_{H}^{*}( {{\Lambda_{H}\Lambda_{H}^{*}} + {\frac{\sigma^{2}}{Q}I}} )}^{- 1}F\;\underset{\_}{r}}}{and}} & {{Equation}\mspace{14mu}(28)} \\{\hat{\underset{\_}{s}} = {{F^{- 1}( {{\Lambda_{H}^{*}\Lambda_{H}} + {\frac{\sigma^{2}}{Q}I}} )}^{- 1}\Lambda_{H}^{*}F\;\underset{\_}{r}}} & {{Equation}\mspace{14mu}(29)}\end{matrix}$respectively. Λ_(H) is a diagonal matrix whose diagonal is F·H(:,1) inwhich H(:,1) denotes the first column of matrix H. The notation (.)*denotes the conjugate operator.

FIG. 2 is a preferred block diagram of the channel equalizer 15. A codematrix C is input into the channel equalizer 15. A Hermitian device 30takes a complex conjugate transpose of the code matrix C, C^(H). Thecode matrix C and its Hermitian are multiplied by a multiplier 32,producing CC^(H). A block FT performed on CC^(H), producing blockdiagonal matrix Λ_(R).

The channel response matrix H is extended and modified by an extend andmodify device 36, producing H^(C). A block FT 38 takes H^(C) andproduces block diagonal matrix Λ_(H). A multiplier multiplies Λ_(H) andΛ_(R) together, producing Λ_(H)Λ_(R). A Hermitian device 42 takes thecomplex conjugate transpose of Λ_(H), producing Λ_(H) ^(H). A multiplier44 multiplies Λ_(H) ^(H) to Λ_(H)Λ_(R), producing Λ_(H)Λ_(R)Λ_(H) ^(H),which is added in adder 46 to σ²I, producing Λ_(H)Λ_(R)Λ_(H) ^(H)+σ²I.

A Cholesky decomposition device 48 produces a Cholesky factor. A blockFT 20 takes a block FT of the received vector r. Using the Choleskyfactor and the FT of r, forward and backward substitution are performedby a forward substitution device 22 and backward substitution device 24.

A conjugation device 56 takes the conjugate of Λ_(H), producing Λ*_(H).The result of backward substitution is multiplied at multiplier 58 toΛ*_(H). A block inverse FT device 60 takes a block inverse FT of themultiplied result, producing ŝ.

According to another embodiment of the present invention, an approximatesolution is provided in which the generalized two-stage data detectionprocess is a block-diagonal-approximation. Theblock-diagonal-approximation includes off-diagonal entries as well asthe diagonal entries in the approximation process.

As an example, the case of four channelization codes is considered. R₀,a combination of four channelization codes, comprises a constant blockdiagonal part, which does not vary with the different combinations ofthe codes, and an edge part which changes with the combinations. Ingeneral R_(o) has the structure of:

$\begin{matrix}{{R_{0} = \begin{bmatrix}c & c & x & x & \; & \; & \; & \; & \; & \; \\c & c & x & x & \; & \; & \; & \; & \; & \; \\{\; x} & x & c & c & \; & \; & \; & \; & \; & \; \\x & x & c & c & \; & \; & \; & \; & \; & \; \\\; & \; & \; & \; & ⋰ & \; & \; & \; & \; & \; \\\; & \; & \; & \; & \; & ⋰ & \; & \; & \; & \; \\\; & \; & \; & \; & \; & \; & c & c & x & x \\\; & \; & \; & \; & \; & \; & c & c & x & x \\\; & \; & \; & \; & \; & \; & {\; x} & x & c & c \\\; & \; & \; & \; & \; & \; & x & x & c & c\end{bmatrix}},} & {{Equation}\mspace{14mu}(30)}\end{matrix}$where elements denoted as c represent constants and are always equal tothe number of channelization codes, i.e., c=K. The elements designatedas x represent some variables whose values and locations vary withdifferent combinations of channelization codes. Their locations varyfollowing certain patterns depending on combinations of codes. As aresult only a few of them are non-zero. When code power is consideredand is not unity power, the element c equals the total power oftransmitted codes. A good approximation of the matrix R₀ is to includethe constant part and ignore the variable part as:

$\begin{matrix}{{\hat{R}}_{0} = {\begin{bmatrix}c & c & \; & \; & \; & \; & \; & \; & \; & \; \\c & c & \; & \; & \; & \; & \; & \; & \; & \; \\\mspace{11mu} & \; & c & c & \; & \; & \; & \; & \; & \; \\\; & \; & c & c & \; & \; & \; & \; & \; & \; \\\; & \; & \; & \; & ⋰ & \; & \; & \; & \; & \; \\\; & \; & \; & \; & \; & ⋰ & \; & \; & \; & \; \\\; & \; & \; & \; & \; & \; & c & c & \; & \; \\\; & \; & \; & \; & \; & \; & c & c & \; & \; \\\; & \; & \; & \; & \; & \; & \mspace{11mu} & \; & c & c \\\; & \; & \; & \; & \; & \; & \; & \; & c & c\end{bmatrix}.}} & {{Equation}\mspace{14mu}(31)}\end{matrix}$

In this case, the approximation {circumflex over (R)}₀ contains only aconstant part. {circumflex over (R)}₀ depends only on the number ofactive codes regardless of which codes are transmitted, and {circumflexover (R)}_(C) can be decomposed as shown in Equation (13). The blockdiagonal of Λ_(R) or F _((Q){circumflex over (R)}) _(C)(:,1:Q) can bepre-calculated using an FFT for different numbers of codes and stored asa look-up table. This reduces the computational complexity by notcomputing F_((Q){circumflex over (R)}) _(C)(:,1 Q) In the case, thatcode power is considered and is not unity power, the element c becomestotal power of active codes, (i.e., c=P_(T) in which P_(T) is the totalpower of active codes). The matrix {circumflex over (R)}₀ can beexpressed as

$\begin{matrix}{{{\hat{R}}_{0} = {P_{avg} \cdot \begin{bmatrix}K & K & \; & \; & \; & \; & \; & \; & \; & \; \\K & K & \; & \; & \; & \; & \; & \; & \; & \; \\\mspace{11mu} & \; & K & K & \; & \; & \; & \; & \; & \; \\\; & \; & K & K & \; & \; & \; & \; & \; & \; \\\; & \; & \; & \; & ⋰ & \; & \; & \; & \; & \; \\\; & \; & \; & \; & \; & ⋰ & \; & \; & \; & \; \\\; & \; & \; & \; & \; & \; & K & K & \; & \; \\\; & \; & \; & \; & \; & \; & K & K & \; & \; \\\; & \; & \; & \; & \; & \; & \mspace{11mu} & \; & K & K \\\; & \; & \; & \; & \; & \; & \; & \; & K & K\end{bmatrix}}},} & {{Equation}\mspace{14mu}(32)}\end{matrix}$where P_(avg) is the average code power obtained by

$P_{avg} = {\frac{P_{T}}{K}.}$In this case, a scaling P_(avg) should be applied in the process.

Other variants of block-diagonal approximation method can be derived byincluding more entries other than the constant block-diagonal part. Thisimproves performance but entails more complexity because by includingvariable entries the FFT for F_((Q))R_(C)(:,1:Q) has to be nowrecalculated as needed if the codes change. The use of more entriesenhances the exact solution as all of the off-diagonal entries areincluded for processing.

At a given number of channelization codes, one can derive the code setsfor different combinations of channelization codes that have commonconstant part of the correlation matrix whose values are equal to thenumber of channelization codes, or the total power of channelizationcodes when the code does not have unity code power. To facilitate thelow complexity implementation, the assignment of channelization codes orresource units can be made following the rules that a code set israndomly picked among the code sets that have common constant part andthose codes in the picked code set are assigned. For example ofassignment of four codes, the code sets [1,2,3,4], [5,6,7,8],[9,10,11,12], . . . have the common constant part in their correlationmatrix. When channel assignment of four codes is made, one of those codesets should be used for optimal computational efficiency.

FIG. 3 is a flow diagram of such a channel code assignment. Code setshaving a constant part are determined, step 100. When assigning codes,the code sets having the constant part are used, step 102.

FIGS. 4A, 4B, 4C and 4D are illustrations of preferred circuits forreducing the complexity in calculating Λ_(R). In FIG. 4A, the number ofcodes processed by the two stage data detector are put in a look-uptable 62 and the Λ_(R) associated with that code number is used. In FIG.4B, the number of codes processed by the two stage data detector are putin a look-up table 64 and an unscaled Λ_(R) is produced. The unscaledΛ_(R) is scaled, such as by a multiplier 66 by P_(avg), producing Λ_(R).

In FIG. 4C, the code matrix C or code identifier is input into a look-uptable 68. Using the look-up table 68, the Λ_(R) is determined. In FIG.4D, the code matrix C or code identifier is input into a look-up table70, producing an unscaled Λ_(R). The unscaled Λ_(R) is scaled, such asby a multiplier 72 by P_(avg), producing Λ_(R).

1. A wireless transmit/receive unit (WTRU) configured to receive andsample wireless signals in a shared spectrum where the wireless signalscomprise encoded symbols, the WTRU comprising: a channel equalizerconfigured to process the received signal samples using an estimatedchannel response matrix H and an estimate of noise variance σ² toproduce a spread signal estimate of the received signals such that:codes of the received signals are processed using a block Fouriertransform (FT) to produce a code block diagonal matrix; the estimatedchannel response matrix H is extended and modified to produce a channelresponse block diagonal matrix; the code block diagonal matrix and thechannel response block diagonal matrix are combined; the received signalsamples are processed using the combined code block diagonal matrix andthe channel response block diagonal matrix with the noise variance σ²and a Cholesky algorithm; and a block inverse FT is performed on aresult of the Cholesky algorithm to produce the spread signal estimateof the received signals; and a despreader configured to process thespread signal estimate of the received signals produced by said channelequalizer to recover the encoded symbols of the received signals.
 2. TheWTRU of claim 1 wherein said channel equalizer includes two multipliers.3. The WTRU of claim 1 wherein said channel equalizer is configured toprocess the received signal samples using the combined code blockdiagonal matrix and the channel response block diagonal matrix with thenoise variance σ² and the Cholesky algorithm by adding a factor of thenoise variance σ² multiplied with an identity matrix.
 4. The WTRU ofclaim 1 wherein said channel equalizer is configured to process codes ofthe received signals using the block Fourier transform (FT) and toproduce the code block diagonal matrix by using a Hermitian device and amultiplier for multiplying a code matrix with a complex conjugatetranspose of the code matrix.
 5. The WTRU of claim 1 wherein saidchannel equalizer is configured to produce the code block diagonalmatrix by inputting a number of codes of interest into a look-up table.6. The WTRU of claim 1 wherein said channel equalizer is configured toproduce the code block diagonal matrix by inputting a number of codes ofinterest into a look-up table and multiplying a resulting diagonal blockmatrix from the look-up table by an average power level.
 7. The WTRU ofclaim 1 wherein said channel equalizer is configured to produce the codeblock diagonal matrix by inputting code identifiers of the receivedsignals into a look-up table.
 8. The WTRU of claim 1 wherein saidchannel equalizer is configured to produce the code block diagonalmatrix by inputting code identifiers of the received signals into alook-up table and multiplying a resulting diagonal block matrix from thelook-up table by an average power level.
 9. The WTRU of claim 1 whereinsaid channel equalizer is configured to produce the code block diagonalmatrix by inputting codes of the received signals into a look-up table.10. The WTRU of claim 1 wherein said channel equalizer is configured toproduce the code block diagonal matrix by inputting codes of thereceived signals into a look-up table and multiplying a resultingdiagonal block matrix from the look-up table by an average power level.11. A method for a wireless transmit/receive unit (WTRU) configured toreceive and sample wireless signals in a shared spectrum where thewireless signals comprise encoded symbols, the method comprising:processing the received signal samples using an estimated channelresponse matrix H and a noise variance σ² to produce a spread signalestimate of the received signals including: processing codes of thereceived signals using a block Fourier transform (FT) and producing acode block diagonal matrix; extending and modifying the channel responsematrix H to produce a channel response block diagonal matrix; combiningthe code block diagonal matrix and the channel response block diagonalmatrix; processing the received signal samples using the combined codeblock diagonal matrix and the channel response block diagonal matrixwith the noise variance σ² and a Cholesky algorithm; and performing ablock inverse FT on a result of the Cholesky algorithm to produce thespread signal estimate of the received signals; and processing thespread signal estimate of the received signals to recover the encodedsymbols of the received signals.
 12. The method of claim 11 wherein saidprocessing the received signal samples using the combined code blockdiagonal matrix and the channel response block diagonal matrix with thenoise variance σ² and the Cholesky algorithm includes adding a factor ofthe noise variance σ² multiplied with an identity matrix.
 13. The methodof claim 11 wherein said processing codes of the received signals usingthe block Fourier transform (FT) and producing the code block diagonalmatrix includes multiplying a code matrix with a complex conjugatetranspose of the code matrix.
 14. The method of claim 11 wherein thecode block diagonal matrix is produced by inputting a number of codes ofinterest into a look-up table.
 15. The method of claim 11 wherein thecode block diagonal matrix is produced by inputting a number of codes ofinterest into a look-up table and multiplying a resulting diagonal blockmatrix from the look-up table by an average power level.
 16. The methodof claim 11 wherein the code block diagonal matrix is produced byinputting code identifiers of the received signals into a look-up table.17. The method of claim 11 wherein the code block diagonal matrix isproduced by inputting code identifiers of the received signals into alook-up table and multiplying a resulting diagonal block matrix from thelook-up table by an average power level.
 18. The method of claim 11wherein the code block diagonal matrix is produced by inputting codes ofthe received signals into a look-up table.